The Sr IT Manager – AI & Data Platforms is responsible for end‑to‑end ownership of delivery, operations, and adoption of Honeywell Aerospace–specific AI and data solutions.

This role leads teams responsible for AI applications, data platforms, and supporting technologies, ensuring seamless delivery from strategy through implementation and steady‑state operations.

Operating as a senior technology and delivery leader, the Sr IT Manager owns program and project execution, technology solution delivery, stakeholder management, and coordination across multiple IT groups.

The role acts as the service owner for assigned AI and data applications and platforms, ensuring reliability, scalability, security, and business value realization.

• 12–15+ years of experience in IT delivery, technology management, or enterprise platform leadership roles
• Proven experience owning end‑to‑end delivery of complex technology programs and platforms
• Strong background in AI, data platforms, analytics, and cloud‑based solutions
• Demonstrated success leading teams and programs in global, matrixed enterprise environments
• Strong stakeholder management and executive communication skills

Education

• Bachelor’s or Master’s degree in Engineering, Computer Science, Information Technology, or a related field

Who Will Succeed in This Role

• Senior leaders who can own end‑to‑end technology implementation and adoption
• Managers with a transformation mindset, capable of driving change across teams and platforms
• Technology leaders who balance delivery rigor with strategic thinking
• Individuals ready to operate at Director‑level influence and serve as a feeder to Director / Senior Director roles

#AERO26

Strategic & Business Alignment

• Translate business and organizational goals into executable IT strategies, roadmaps, and delivery plans for AI and data platforms
• Partner with business leaders to define and evolve technology roadmaps aligned to Honeywell Aerospace priorities
• Act as a senior technology advisor, ensuring AI and data initiatives directly support measurable business outcomes

2. Technology Leadership & End‑to‑End Delivery

• Provide end‑to‑end ownership of AI and data programs, platforms, and applications
• Lead delivery across AI solutions, data engineering, analytics platforms, and supporting services
• Ensure predictable delivery, quality, and value realization across programs and portfolios
• Oversee program governance, risk management, dependency management, and issue resolution across teams

3. Platform, Application & Service Ownership

• Act as the service owner for assigned AI and data platforms and applications
• Ensure platforms are stable, secure, scalable, and aligned to enterprise architecture standards
• Support and evolve technical solutions and platforms across the AI and data ecosystem
• Drive continuous improvement in platform reliability, performance, and usability

4. Cross‑Functional Coordination & Delivery Integration

• Coordinate delivery across multiple IT groups, including:

• Data engineering

• AI/ML teams

• Cloud and platform teams

• Security, architecture, and operations

• Ensure seamless integration of solutions across enterprise systems

• Resolve cross‑team dependencies and delivery constraints proactively

5.

Operational Excellence & Governance:

• Establish and enforce IT governance models covering service delivery, controls, and operational performance
• Ensure compliance with enterprise architecture, cybersecurity, data governance, and regulatory requirements
• Drive continuous improvement of delivery processes, operating models, and performance metrics

6. People, Team & Talent Leadership

• Lead and develop managers, technical leads, and senior individual contributors
• Build high‑performing teams with clear accountability for delivery and outcomes
• Support talent development, succession planning, and leadership readiness
• Foster a culture of accountability, inclusion, and continuous improvement

7. Financial, Resource & Supplier Management

• Own budgets, AOP commitments, and cost optimization for assigned platforms and programs
• Plan and manage resource capacity, including internal teams and system integration partners
• Manage supplier and partner relationships, supporting flux and surge delivery models
• Balance delivery speed with cost, quality, security, and compliance

8.

Stakeholder & Executive Engagement:

• Serve as a senior IT partner to business leaders, enterprise architecture, AI, data, and platform teams
• Provide executive‑level status reporting, risk visibility, and decision support
• Influence enterprise‑wide decisions with an enterprise mindset, beyond functional silos

9. Risk, Compliance & Controls

• Ensure AI and data initiatives comply with enterprise risk, regulatory, cybersecurity, and data governance standards
• Proactively identify and mitigate technology, delivery, and operational risks
• Support audits, governance reviews, and compliance assessments as part of senior management accountability